问题描述
我对purrr :: pmap有一些疑问,以便在nested.data.frame中绘制ggplot的多个图.
I have some questions about purrr::pmap to make multiple plots of ggplot in nested.data.frame.
我可以使用purrr :: map2在代码下面运行,并且可以在nested.data.frame中制作多图(2个图).
I can run below code without problem by using purrr::map2 and I can make multiplots(2 plots) in nested.data.frame.
例如,我在R中使用了虹膜数据集.
As a example, I used the iris dataset in R.
library(tidyverse)
iris0 <- iris
iris0 <-
iris0 %>%
group_by(Species) %>%
nest() %>%
mutate(gg1 = purrr::map(data, ~ ggplot(., aes(Sepal.Length, Sepal.Width)) + geom_point())) %>%
mutate(gg2 = purrr::map(data, ~ ggplot(., aes(Sepal.Length, Petal.Width)) + geom_point())) %>%
mutate(g = purrr::map2(gg1, gg2, ~ gridExtra::grid.arrange(.x, .y)))
但是,当我要绘制两个以上的图时,我无法像下面的代码一样使用purrr :: pmap来解决问题.
But, when I want to plot more than 2 plots, I can't solve using purrr::pmap like below code.
iris0 <-
iris0 %>%
group_by(Species) %>%
nest() %>%
mutate(gg1 = purrr::map(data, ~ ggplot(., aes(Sepal.Length, Sepal.Width)) + geom_point())) %>%
mutate(gg2 = purrr::map(data, ~ ggplot(., aes(Sepal.Length, Petal.Width)) + geom_point())) %>%
mutate(gg3 = purrr::map(data, ~ ggplot(., aes(Sepal.Length, Petal.Length)) + geom_point())) %>%
mutate(g = purrr::pmap(gg1, gg2,gg3, ~ gridExtra::grid.arrange(.x, .y, .z)))
> Error in mutate_impl(.data, dots) : Index 1 is not a length 1 vector
nested.data.frame中是否有解决此问题的方法?请给我一些建议或答案.
Is there is a way of solving this problem in nested.data.frame ?Please give me some advices or answers.
推荐答案
purrr::pmap
接受(至少)两个参数:
purrr::pmap
takes (at least) two arguments:
pmap(.l, .f, ...)
其中
.l: A list of lists. The length of '.l' determines the number of
arguments that '.f' will be called with. List names will be
used if present.
.f: A function, formula, or atomic vector.
此外,.x
和.y
仅适用于两个参数,但是(在同一手册页中)它表示For more arguments, use '..1', '..2', '..3' etc
.
Further, .x
and .y
work well for only two arguments, but (in the same man page) it says For more arguments, use '..1', '..2', '..3' etc
.
为了提高可读性(并提高效率),我将对mutate
的所有单个调用合并为一个;您可以根据需要将它们分开(特别是如果代码比在此简化示例中显示的更多):
For readability (and a little efficiency), I'll combine all of the individual calls to mutate
into one; you can keep them separate if needed (esp if there is more to the code than you show in this reduced example):
library(dplyr)
library(tidyr)
library(purrr)
library(ggplot2)
iris0 <- iris %>%
group_by(Species) %>%
nest() %>%
mutate(
gg1 = purrr::map(data, ~ ggplot(., aes(Sepal.Length, Sepal.Width)) + geom_point()),
gg2 = purrr::map(data, ~ ggplot(., aes(Sepal.Length, Petal.Width)) + geom_point()),
gg3 = purrr::map(data, ~ ggplot(., aes(Sepal.Length, Petal.Length)) + geom_point()),
g = purrr::pmap(list(gg1, gg2, gg3), ~ gridExtra::grid.arrange(..1, ..2, ..3))
)
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